Kamyar Moshksar
“On Asynchronous Interference Channels”
The first part of the thesis studies a decentralized network of separate transmitter- receiver (Tx- Rx) pairs. The users are asynchronous meaning there exists a mutual delay between their transmitted codewords. The network being decentralized, different users are unaware of each other’s preamble sequences. As such, the receivers can not determine the exact positions of interference bursts. We introduce a learning technique based on piecewise-linear regression where it is shown how each Rx successfully estimates the number of interferers and the mutual delays. The estimates for the mutual delays are not perfect, however, they are reliable enough to guarantee successful decoding.
The second part of the thesis addresses a centralized Gaussian interference channel of two Tx-Rx pairs under stochastic data arrival (GIC-SDA). The information bits arrive at the transmitters accord- ing to independent and asynchronous Bernoulli processes (Tx- Tx asynchrony). The transmissions are asynchronous (Tx-Rx asynchrony) in the sense that a Tx immediately sends a codeword to its Rx when there are enough information bits gathered in its buffer. Such immediate style of transmission is in contrast to the conventional synchronous style of transmission. In a setting where the transmitters only know the statistics of Tx-Tx asynchrony, it is shown how each user designs its codebook rate in order to maximize the probability of successful decoding at the receivers. An achievable region is char- acterized for the codebook rates in a two-user GIC-SDA under the requirements that the transmissions be immediate and the receivers treat interference as noise. This region is described as the union of uncountably many polyhedrons and is in general disconnected and non-convex due to infeasibility of time sharing.
MC 5417